1. Field
The present invention relates generally to data communication, and more specifically to techniques for time-domain transmit and receive processing with channel eigen-mode decomposition for multiple-input multiple-output (MIMO) communication systems.
2. Background
In a wireless communication system, an RF modulated signal from a transmitter may reach a receiver via a number of propagation paths. The characteristics of the propagation paths typically vary over time due to a number of factors such as fading and multipath. To provide diversity against deleterious path effects and improve performance, multiple transmit and receive antennas may be used. If the propagation paths between the transmit and receive antennas are linearly independent (i.e., a transmission on one path is not formed as a linear combination of the transmissions on other paths), which is generally true to at least an extent, then the likelihood of correctly receiving a data transmission increases as the number of antennas increases. Generally, diversity increases and performance improves as the number of transmit and receive antennas increases.
A multiple-input multiple-output (MIMO) communication system employs multiple (NT) transmit antennas and multiple (NR) receive antennas for data transmission. A MIMO channel formed by the NT transmit and NR receive antennas may be decomposed into NC independent channels, with NC≦min {NT, NR}. Each of the NC independent channels is also referred to as a spatial subchannel of the MIMO channel and corresponds to a dimension. The MIMO system can provide improved performance (e.g., increased transmission capacity) if the additional dimensionalities created by the multiple transmit and receive antennas are utilized.
The spatial subchannels of a wideband MIMO system may experience different channel conditions (e.g., different fading and multipath effects) across its bandwidth and may achieve different signal-to-noise-and-interference ratios (SNRs) at different frequencies (i.e., different frequency bins or subbands) of the overall system bandwidth. Consequently, the number of information bits per modulation symbol (i.e., the data rate) that may be transmitted at different frequency bins of each spatial subchannel for a particular level of performance may be different from bin to bin. Moreover, the channel conditions typically vary with time. As a result, the supported data rates for the bins of the spatial subchannels also vary with time.
To combat the frequency selective nature of the wideband channel (i.e., different channel gains for different bins), orthogonal frequency division multiplexing (OFDM) may be used to effectively partition the system bandwidth into a number of (NF) subbands (which may be referred to as frequency bins or subchannels). In OFDM, each frequency subchannel is associated with a respective subcarrier upon which data may be modulated, and thus may also be viewed as an independent transmission channel.
A key challenge in a coded communication system is the selection of the appropriate data rates and coding and modulation schemes to be used for a data transmission based on channel conditions. The goal of this selection process is to maximize throughput while meeting quality objectives, which may be quantified by a particular frame error rate (FER), certain latency criteria, and so on.
One straightforward technique for selecting data rates and coding and modulation schemes is to “bit load” each frequency bin of each spatial subchannel according to its transmission capability, which may be quantified by the bin's short-term average SNR. However, this technique has several major drawbacks. First, coding and modulating individually for each bin of each spatial subchannel can significantly increase the complexity of the processing at both the transmitter and receiver. Second, coding individually for each bin may greatly increase coding and decoding delay. And third, a high feedback rate may be needed to send channel state information (CSI) indicative of the channel conditions (e.g., the gain, phase and SNR) of each bin.
There is therefore a need in the art for achieving high throughput in a coded MIMO system without having to individually code different frequency bins of the spatial subchannels.